Saved in:
| Main Authors: | Liu, Jiading, Shi, Lei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.02376 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression
by: Liu, Jiading, et al.
Published: (2022)
by: Liu, Jiading, et al.
Published: (2022)
A Theory of Nonparametric Covariance Function Estimation for Discretely Observed Data
by: Terada, Yoshikazu, et al.
Published: (2026)
by: Terada, Yoshikazu, et al.
Published: (2026)
Discrete Distribution Networks
by: Yang, Lei
Published: (2023)
by: Yang, Lei
Published: (2023)
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
by: Luo, Yuankai, et al.
Published: (2024)
by: Luo, Yuankai, et al.
Published: (2024)
Joint Registration and Conformal Prediction for Partially Observed Functional Data
by: Wang, Fangyi, et al.
Published: (2025)
by: Wang, Fangyi, et al.
Published: (2025)
Generative Assignment Flows for Representing and Learning Joint Distributions of Discrete Data
by: Boll, Bastian, et al.
Published: (2024)
by: Boll, Bastian, et al.
Published: (2024)
DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
by: Gai, Jiading, et al.
Published: (2026)
by: Gai, Jiading, et al.
Published: (2026)
Distributed Gradient Descent for Functional Learning
by: Yu, Zhan, et al.
Published: (2023)
by: Yu, Zhan, et al.
Published: (2023)
Uncovering Utility Functions from Observed Outcomes
by: Grzeskiewicz, Marta
Published: (2025)
by: Grzeskiewicz, Marta
Published: (2025)
An Improved Algorithm for Learning Drifting Discrete Distributions
by: Mazzetto, Alessio
Published: (2024)
by: Mazzetto, Alessio
Published: (2024)
Modeling Partially Observed Nonlinear Dynamical Systems and Efficient Data Assimilation via Discrete-Time Conditional Gaussian Koopman Network
by: Chen, Chuanqi, et al.
Published: (2025)
by: Chen, Chuanqi, et al.
Published: (2025)
Symbolic Density Estimation for Discrete Distributions
by: Liu, Ziwen, et al.
Published: (2026)
by: Liu, Ziwen, et al.
Published: (2026)
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
by: Lou, Aaron, et al.
Published: (2023)
by: Lou, Aaron, et al.
Published: (2023)
COMPILED: Deep Metric Learning for Defect Classification of Threaded Pipe Connections using Multichannel Partially Observed Functional Data
by: Du, Juan, et al.
Published: (2024)
by: Du, Juan, et al.
Published: (2024)
Simplified and Generalized Masked Diffusion for Discrete Data
by: Shi, Jiaxin, et al.
Published: (2024)
by: Shi, Jiaxin, et al.
Published: (2024)
Learning Preference from Observed Rankings
by: Chen, Yu-Chang, et al.
Published: (2026)
by: Chen, Yu-Chang, et al.
Published: (2026)
Drift Estimation for Diffusion Processes Using Neural Networks Based on Discretely Observed Independent Paths
by: Zhao, Yuzhen, et al.
Published: (2025)
by: Zhao, Yuzhen, et al.
Published: (2025)
Uncertainty-Based Extensible Codebook for Discrete Federated Learning in Heterogeneous Data Silos
by: Zhang, Tianyi, et al.
Published: (2024)
by: Zhang, Tianyi, et al.
Published: (2024)
Learning from Snapshots of Discrete and Continuous Data Streams
by: Devulapalli, Pramith, et al.
Published: (2024)
by: Devulapalli, Pramith, et al.
Published: (2024)
Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
by: Wang, Yinsong, et al.
Published: (2026)
by: Wang, Yinsong, et al.
Published: (2026)
Efficient Data Distribution Estimation for Accelerated Federated Learning
by: Wang, Yuanli, et al.
Published: (2024)
by: Wang, Yuanli, et al.
Published: (2024)
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
by: Liu, Hao, et al.
Published: (2024)
by: Liu, Hao, et al.
Published: (2024)
Spectral Clustering for Discrete Distributions
by: Wang, Zixiao, et al.
Published: (2024)
by: Wang, Zixiao, et al.
Published: (2024)
Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data
by: Ou, Jingyang, et al.
Published: (2024)
by: Ou, Jingyang, et al.
Published: (2024)
Discrete Differential Principle for Continuous Smooth Function Representation
by: Wang, Guoyou, et al.
Published: (2025)
by: Wang, Guoyou, et al.
Published: (2025)
Data-Assimilated Model-Based Reinforcement Learning for Partially Observed Chaotic Flows
by: Ozan, Defne E., et al.
Published: (2025)
by: Ozan, Defne E., et al.
Published: (2025)
DGNet: Discrete Green Networks for Data-Efficient Learning of Spatiotemporal PDEs
by: Tan, Yingjie, et al.
Published: (2026)
by: Tan, Yingjie, et al.
Published: (2026)
Leveraging Discrete Function Decomposability for Scientific Design
by: Bowden, James C., et al.
Published: (2025)
by: Bowden, James C., et al.
Published: (2025)
Learning to Discretize Denoising Diffusion ODEs
by: Tong, Vinh, et al.
Published: (2024)
by: Tong, Vinh, et al.
Published: (2024)
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation
by: Liu, Zhishuai, et al.
Published: (2024)
by: Liu, Zhishuai, et al.
Published: (2024)
Optimal Particle-based Approximation of Discrete Distributions (OPAD)
by: Afshar, Hadi Mohasel, et al.
Published: (2024)
by: Afshar, Hadi Mohasel, et al.
Published: (2024)
Distillation of Discrete Diffusion by Exact Conditional Distribution Matching
by: Gao, Yansong, et al.
Published: (2025)
by: Gao, Yansong, et al.
Published: (2025)
StablePCA: Distributionally Robust Learning of Shared Representations from Multi-Source Data
by: Wang, Zhenyu, et al.
Published: (2025)
by: Wang, Zhenyu, et al.
Published: (2025)
Unified Discrete Diffusion for Categorical Data
by: Zhao, Lingxiao, et al.
Published: (2024)
by: Zhao, Lingxiao, et al.
Published: (2024)
Electric Currents for Discrete Data Generation
by: Kolesov, Alexander, et al.
Published: (2025)
by: Kolesov, Alexander, et al.
Published: (2025)
Learning-Augmented Ski Rental with Discrete Distributions: A Bayesian Approach
by: Kang, Bosun, et al.
Published: (2025)
by: Kang, Bosun, et al.
Published: (2025)
Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning
by: Zhu, Yuanyang, et al.
Published: (2024)
by: Zhu, Yuanyang, et al.
Published: (2024)
Data Distribution-based Curriculum Learning
by: Chaudhry, Shonal, et al.
Published: (2024)
by: Chaudhry, Shonal, et al.
Published: (2024)
A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
by: Yan, Yunlu, et al.
Published: (2023)
by: Yan, Yunlu, et al.
Published: (2023)
Clustering Mixtures of Discrete Distributions: A Note on Mitra's Algorithm
by: Seif, Mohamed, et al.
Published: (2024)
by: Seif, Mohamed, et al.
Published: (2024)
Similar Items
-
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression
by: Liu, Jiading, et al.
Published: (2022) -
A Theory of Nonparametric Covariance Function Estimation for Discretely Observed Data
by: Terada, Yoshikazu, et al.
Published: (2026) -
Discrete Distribution Networks
by: Yang, Lei
Published: (2023) -
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
by: Luo, Yuankai, et al.
Published: (2024) -
Joint Registration and Conformal Prediction for Partially Observed Functional Data
by: Wang, Fangyi, et al.
Published: (2025)